[Big data from clinical routine]

Z Rheumatol. 2018 Apr;77(3):209-218. doi: 10.1007/s00393-018-0424-7.
[Article in German]

Abstract

Background: Over the past 100 years, evidence-based medicine has undergone several fundamental changes. Through the field of physiology, medical doctors were introduced to the natural sciences. Since the late 1940s, randomized and epidemiological studies have come to provide the evidence for medical practice, which led to the emergence of clinical epidemiology as a new field in the medical sciences. Within the past few years, big data has become the driving force behind the vision for having a comprehensive set of health-related data which tracks individual healthcare histories and consequently that of large populations.

Objectives: The aim of this article is to discuss the implications of data-driven medicine, and to examine how it can find a place within clinical care.

Materials and methods: The EU-wide discussion on the development of data-driven medicine is presented.

Results: The following features and suggested actions were identified: harmonizing data formats, data processing and analysis, data exchange, related legal frameworks and ethical challenges. For the effective development of data-driven medicine, pilot projects need to be conducted to allow for open and transparent discussion on the advantages and challenges. The Federal Ministry of Education and Research ("Bundesministerium für Bildung und Forschung," BMBF) Arthromark project is an important example. Another example is the Medical Informatics Initiative of the BMBF.

Discussion and conclusion: The digital revolution affects clinic practice. Data can be generated and stored in quantities that are almost unimaginable. It is possible to take advantage of this for development of a learning healthcare system if the principles of medical evidence generation are integrated into innovative IT-infrastructures and processes.

Keywords: Data collection; Evidence-based medicine; Information processing; Medical informatics; Patient data privacy.

Publication types

  • Review

MeSH terms

  • Big Data*
  • Delivery of Health Care / trends
  • Evidence-Based Medicine / trends*
  • Forecasting
  • Germany
  • Humans
  • Medical Records Systems, Computerized / trends*
  • Patient Generated Health Data / trends*